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A Probabilistic Re-Intepretation of Confidence Scores in Multi-Exit Models
In this paper, we propose a new approach to train a deep neural network with multiple intermediate auxiliary classifiers, branching from it. These ‘multi-exits’ models can be used to reduce the inference time by performing early exit on the intermediate branches, if the confidence of the prediction...
Autores principales: | Pomponi, Jary, Scardapane, Simone, Uncini, Aurelio |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774619/ https://www.ncbi.nlm.nih.gov/pubmed/35052027 http://dx.doi.org/10.3390/e24010001 |
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